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Record W2382559638

Management of Canadian S&T Programs and Its Conflicts of Interest Avoiding Mechanism(I)

2013· article· en· W2382559638 on OpenAlexaboutno aff
Kong Xin-xi

Bibliographic record

VenueGlobal Science,Technology and Economy Outlook · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Mechanism (biology)BusinessSet (abstract data type)Public relationsKnowledge managementPublic administrationPolitical scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

The effective management of ST programs and mechanism of conflicts of interest avoiding are important guarantees for promoting national ST innovation.Canadian federal government has formed a complete set of program management approaches in supporting scientific research through years of practices,and now is actively exploring approaches to support enterprise innovation.Based on several typical science and technology programs of Canada,this paper systematically analyzes the programs' objective,assessment criteria,assessment procedure,funds management approach,and conflicts of interest avoiding mechanism,and summarizes experiences of Canadian ST program management.Finally,this paper also analyzes characteristics of Canada in supporting businesses innovation,as well as the challenges the federal government are confronting during the transformation from traditional ST policy to innovation-oriented policy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0080.003
Scholarly communication0.0100.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.229
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainIncentives
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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